Emergency Radiology最新文献

Introduction: Traumatic Brain Injury (TBI) is a major cause of morbidity and mortality worldwide, with isolated blunt TBIs presenting unique clinical challenges. Despite extensive research, limited studies have examined how specific TBI subtypes, subdural hematoma (SDH), subarachnoid hemorrhage (SAH), epidural hemorrhage (EDH), diffuse axonal injury (DAI), and contusions-affect critical outcomes such as in-hospital mortality, ICU length of stay (LOS), and ventilation duration. Understanding these associations is essential for improving patient management and resource allocation.

Objective: This study aims to assess the impact of TBI subtype and size on clinical outcomes, including in-hospital mortality, ICU LOS, and ventilation days, in adult patients with isolated blunt TBI and skull fractures.

Methods: A retrospective cohort analysis was conducted using the ACS-TQIP-PUF (2017-2022). Logistic and linear regression models analyzed TBI subtype, size, demographics, comorbidities, and injury characteristics in patients aged ≥ 15 years with isolated blunt TBI and skull fractures. Polytrauma cases were excluded.

Results: Among 64,111 patients, SDH > 8 mm had the highest association with in-hospital mortality (OR 4.89, p <.01). Larger SDH (> 8 mm), contusions (> 2 cm), and SAH correlated with extended ICU LOS, with DAI leading to the longest ICU stays (+ 5.73 days, p <.01) and ventilation days (+ 8.40 days, p <.01).

Conclusion: TBI subtype and size significantly influence patient outcomes. SDH > 8 mm poses the highest mortality risk, while DAI results in prolonged ICU stays and ventilation. These findings highlight the need for targeted management strategies to optimize care for TBI patients.

Levels of evidence: Level III, retrospective/epidemiological.

Purpose: This study aimed to evaluate and compare the diagnostic performance and image quality of deep learning reconstruction (DLR) with hybrid iterative reconstruction (Hybrid IR) and filtered back projection (FBP) in contrast-enhanced CT venography for deep vein thrombosis (DVT).

Methods: A retrospective analysis was conducted on 51 patients who underwent lower limb CT venography, including 20 with DVT lesions and 31 without DVT lesions. CT images were reconstructed using DLR, Hybrid IR, and FBP. Quantitative image quality metrics, such as contrast-to-noise ratio (CNR) and image noise, were measured. Three radiologists independently assessed DVT lesion detection, depiction of DVT lesions and normal structures, subjective image noise, artifacts, and overall image quality using scoring systems. Diagnostic performance was evaluated using sensitivity and area under the receiver operating characteristic curve (AUC). The paired t-test and Wilcoxon signed-rank test compared the results for continuous variables and ordinal scales, respectively, between DLR and Hybrid IR as well as between DLR and FBP.

Results: DLR significantly improved CNR and reduced image noise compared to Hybrid IR and FBP (p < 0.001). AUC and sensitivity for DVT detection were not statistically different across reconstruction methods. Two readers reported improved lesion visualization with DLR. DLR was also rated superior in image quality, normal structure depiction, and noise suppression by all readers (p < 0.001).

Conclusions: DLR enhances image quality and anatomical clarity in CT venography. These findings support the utility of DLR in improving diagnostic confidence and image interpretability in DVT assessment.

Purpose: Artificial Intelligence (AI) algorithms in radiology are currently deployed as tools to augment radiologists rather than autonomous readers. An augmentative tool should improve performance above and beyond the baseline performance achieved by the user alone. We conducted a meta-analysis to elucidate the added value of augmentative AI to radiologists for detecting Pulmonary Embolism (PE) on CT scan.

Methods: Using PRISMA guidelines, studies in which both AI and Human Interpreter (HI) assessed CT scans for pulmonary emboli were selected. Data extracted from these studies were used to compare diagnostic performance of AI and HI with an emphasis on the performance of AI above and beyond that of HI.

Results: Both HI and AI performed similarly with no statistically significant difference in the pooled estimates of sensitivity, specificity, PPV, NPV and accuracy. Subsequent analysis focusing on the differences between performance of AI and HI within each study, followed by pooled estimate, also did not demonstrate any significant difference (p < 0.05).

Conclusions: In a meta-analysis of nearly sixteen thousand CTs, AI and HI had similar performance for detection of pulmonary emboli. On one hand, this buttresses AI's use for triaging and for second reads. On the other hand, the outcomes may or may not be different when AI is added-on. The findings of this meta-analysis can be used to re-examine the use-scenarios of AI and to re-calibrate its value proposition.

Purpose: Diagnosis of pyelonephritis can be challenging in young children. Our purpose is to evaluate the incidence and characteristics of CT-diagnosed pyelonephritis that was not clinically suspected in children under 7 years of age.

Methods: We retrospectively identified children < 7 years with CT diagnosis of pyelonephritis between 2011 and 2024. Demographic, clinical, and laboratory data were extracted from the medical record. One pediatric radiologist reviewed all CT scans and recorded the findings. Wilcoxon rank sum tests were used to compare age with clinically unsuspected pyelonephritis and negative urinalysis; Chi-square tests compared extent of pyelonephritis with renal atrophy and dilated (grades 3-5) VUR.

Results: 104 children (mean age 4.8 years; 79 females) met inclusion. 92/104 (88.5%) had no UTI history; 34/104 (32.7%) had urinary symptoms. Pyelonephritis was clinically unsuspected in 53/104 (51.0%), with no age group difference (p = 0.579). Urinalysis was negative in 17/104 (16.3%). 26 children received antibiotics prior to sampling. CT showed pyelonephritis in 126 kidneys (48 right, 34 left, 22 bilateral); 7 children had renal abscesses. Renal scarring developed in 11/47 with follow up renal imaging (23.4%). VUR was found in 41/51 with voiding cystourethrogram (80.4%), including 26 with grade 3-5 VUR. No association was found between extent of renal involvement and atrophy/scarring (p = 0.978) or VUR (p = 0.751).

Conclusion: CT-diagnosed pyelonephritis in young children is often clinically unsuspected and may present with negative urine tests. Follow-up US and voiding cystourethrogram are warranted to assess for scarring and VUR, even in the absence of prior UTI.

Purpose: To evaluate the efficacy and complications of absorbable haemostatic gelatin uterine artery embolisation for symptomatic acquired uterine arterio-venous malformation (UAVM).

Methods: All the adult female patients who had acute urogenital bleeding due to UAVM confirmed on ultrasound and received uterine artery embolisation (UAE) for UAVM in a tertiary institution between January 2000 and October 2024 were included. Patients who had UAE for other causes were excluded. Causes of UAVM, embolic agents used, procedural success, recurrent genital bleeding, and complications like pulmonary embolism and groin bleeding were recorded.

Results: Seven female patients (mean age: 34 years) with 8 UAE procedures were included, with three postpartum and four after miscarriages. The mean length of follow-up after UAE was 50 months. Absorbable gelatin was used in six patients, and polyvinyl alcohol (PVA) particles were used in one patient. 5/6 patients (83.3%) had successful UAE with absorbable haemostatic gelatin. There were no procedure-related complications, including pulmonary embolism and uterine infarcts. Only one patient required a repeated UAE 33 days later for recurrent vaginal bleeding, which required sodium tetradecyl sulphate injection and microcoils during embolisation.

Conclusion: Acquired UAVM is very rare but life-threatening. Absorbable haemostatic gelatin, a temporary embolic agent, appears safe and effective in treating UAVM with uterine preservation. It eliminates the potential risk of uterine infarction that might occur with permanent embolic agents.

Purpose: Occipital condyle fractures (OCFs) are classified by the Anderson and Montesano system into Type I (comminuted, minimally displaced), Type II (stable, associated with basilar skull fractures), and Type III (unstable avulsion fractures). We retrospectively analyzed 24,986 cervical spine CT examinations of emergency department patients over five years to determine the incidence and characteristics of OCFs, mechanism of injury, and associated intracranial and cervical spine injuries.

Methods and materials: The study was IRB-approved and HIPAA compliant. We retrospectively reviewed the CT brain and CT cervical spine reports performed from July 2018 to August 2023. Variables collected included age, sex, clinical presentation, coincident brain and cervical spine injuries, treatments, and OCF classifications.

Results: Sixty-three of 24,986 patients (0.25%) had OCFs, predominantly male (41 males, 22 females), with an average age of 51.1 years; 22/63 (34.9%) occurred in asymptomatic patients. Concurrent injuries included cervical spine fractures (33.3%) at C1 and C2 and intracranial injuries (47.6%), mostly subarachnoid and subdural hemorrhages. OCFs were categorized into Anderson-Montesano Type I (9 cases), Type II (24 cases), and Type III (30 cases), with unstable Type III fractures more common in MVC victims; stable fractures had higher rates of intracranial injuries. There were no significant differences in morbidity, mortality, or concurrent cervical spine or chest/abdominal/pelvic findings between stable and unstable OCFs.

Conclusion: The study highlights the importance of comprehensive imaging and evaluation in trauma cases to identify OCFs, even in asymptomatic patients, with a high rate of concurrent C1-2 and intracranial injuries.

Clinical relevance/application: Being aware of occipital condyle fractures, types, and complications is important in the emergency radiology evaluation of trauma patients, especially given high rates of C1-2 fractures and intracranial bleeds.

Purpose: To evaluate the range and severity of acute injuries sustained by patients over 60 years old presenting to a tertiary centre emergency department following a fall from standing height on computed tomography (CT) and the appropriate imaging protocol to utilise in this cohort.

Methods: We conducted a retrospective review of all CT thorax requests for patients over 60 years old following a fall from standing height between 2019 and 2020. CT requests and reports were extracted from the radiology information system and appropriate scans identified for inclusion. Clinical data was extracted from electronic patient records.

Results: 349 patients over 60 years old underwent a CT scan following a fall from standing height. Of these, 204 underwent a non-contrast CT chest and 145 underwent contrast enhanced CT thorax abdomen pelvis. 178 (51%) of patients had an acute finding on thoracic CT; 170 patients had 1 or more rib fractures, 16 had radiological flail segments, 30 patients had a pneumothorax and 44 had a haemothorax. 36 patients sustained an acute fracture other than rib fracture. 45 patients with rib fractures on CT also underwent concurrent CXR; however, only 15 of these patients had rib fractures visible on CXR. Out of the 145 patients who underwent abdominal-pelvic CT, 23 (16%) patients had an acute traumatic finding.

Conclusion: Patients aged over 60 are at high risk of sustaining thoracic injury following a fall from standing height. Acute findings were identified in over half of elderly patients who underwent thoracic CT due to clinical suspicion of thoracic injury. Rib fractures were the most common finding, and were often missed on concurrent CXR. Comparatively, acute abdominal injury was rare in this cohort. These results emphasize the importance of CT thorax imaging in accurately diagnosing fall-related injuries in older adults.

Objectives: To evaluate the predictive value of two radiological markers, the spot sign and leakage sign, for spontaneous intracranial hematoma expansion and their association with clinical outcomes, including neurological deterioration and in-hospital mortality.

Materials & methods: This prospective single-center study included 94 adult patients with spontaneous intraparenchymal hemorrhagic stroke, confirmed by non-enhanced CT (NECT) and contrast-enhanced CT (CECT) in the arterial phase. Hematoma volumes and spot/leakage signs were assessed using standardized imaging protocols and analyzed by two blinded neuroradiologists. Clinical and radiological data were evaluated using multivariate analyses, with survival outcomes compared via Kaplan-Meier curves. Statistical significance was set at p ≤ 0.05.

Results: Among 94 patients, hematoma expansion occurred in 42%, neurological deterioration in 15.5%, and mortality in 39.4%. The leakage sign was the strongest independent predictor of hematoma expansion (OR: 9.27, 95% CI: 2.95-29.20), neurological deterioration (OR: 26.67, 95% CI: 1.62-47.39), and mortality (OR: 7.56, 95% CI: 2.97-19.25). The spot and leakage signs demonstrated high specificity for predicting outcomes, with the leakage sign showing greater sensitivity for hematoma expansion. Patients with a positive leakage sign had significantly lower median survival (6 days) compared to those with a positive spot sign alone (54 days) or no signs (110 days, p < 0.001).

Conclusion: The leakage sign demonstrated greater sensitivity and comparable specificity to the spot sign for predicting hematoma expansion. Both signs were associated with neurological deterioration and in-hospital mortality, with the leakage sign showing a stronger predictive value.

Purpose: The aim of our study was to assess the frequency and detection rate of dental trauma and maxillofacial injuries (DTMI) in high-energy polytrauma patients undergoing total-body computed tomography (TBCT) and to estimate how often they are correctly reported by the radiologists.

Methods: This retrospective study included 611 patients who underwent TBCT following high-energy trauma between July 2024 and February 2025. DTMI findings were analyzed based on initial radiology reports and retrospective image review.

Results: DTMI was identified in 124 of 611 patients (20.2%), of which only 76 cases (61%) were reported at admission. Dental trauma was significantly underreported (76% missed rate), with only 12 of 50 cases (24%) initially recognized. In contrast, maxillofacial injuries were detected in 75 of 97 cases (77,3%). Most DTMI-positive patients (82/124, 66%) had additional traumatic findings, including cranial or spinal injuries (33/124, 26.6%) and multi-district trauma (29/124, 23.4%). Only 20 patients (16%) presented with isolated facial trauma. A small subgroup (18/124, 14.5%) had DTMI with no other traumatic findings, suggesting possible oversight in the absence of overt injury. Underreporting rates were slightly higher during night shifts (55%) compared to daytime (48%), though not statistically significant (χ² = 0.654, p > 0.05). DTMI was more common in males (ratio 1.79:1).

Conclusion: DTMI, especially dental trauma, is frequently underdiagnosed in the acute trauma setting. Improved detection may be achieved through dedicated imaging protocols, increased radiologists awareness, and AI-based support tools.